12 research outputs found
EVALUASI MODEL SIMULASI HISTORIS VALUE AT RISK PORTFOLIO DENGAN METODE CHRISTOFFERSEN
According to Christoffersen (1998), the property of a good VaR model are correct unconditional coverage, correct independence test and correct conditional coverage. Unconditional coverage test calculate how much violations exceed the VaR. If average of violations exceeded the percentage of VaR value, so it is called bad model. Independence test calculate how much violations clustering. If a model VaR has much violations clustering, so it is called bad model, because the risk of bankruptcy would be much higher than if the violations came scattered randomly through time. Conditional coverage test is simultaneously testing both unconditional coverage and independence test. Backtesting base on Christoffersen method different way with Kupiec method. Kupiec method only test on unconditional coverage, so Christoffersen method more complete than Kupiec method
PENENTUAN HARGA OPSI CALL FLOATING STRIKE LOOKBACK EROPA MENGGUNAKAN MODEL POHON BINOMIAL
This thesis explains about pricing European floating strike lookback call
options using a binomial tree model with combinatorial approach. The basic idea
is to divide the price paths reaching node terminal into groups by their extreme
stock prices. The price paths in the same group have the same payoff. Then the
value contributed by grups are evaluated. For evaluating the value contributed by
terminal node, two different cases are considered. The value contributed by
terminal node is the sum of the value contributed by grups. The value of a floating
strike lookback call option is the sum of the values contributed by all the terminal
nodes
PENENTUAN HARGA OPSI COMPOUND CALL ON CALL EROPA
In stock and options trading, stock price movements are often up and
down. This raises concerns investor to invest in the financial sector. European
Call on Call Compound Option is a option on the option. European Call on Call
Compound Options will protect and minimize the loss of the option holder if the
stock price falls below the market price of the contract. This thesis will discuss the
option price calculation Compound Call on Call Europe with the Black-Scholes
model approach and the bivariate normal distribution
PENDEKATAN HIERARCHICAL LIKELIHOOD UNTUK MODEL LOGNORMAL FRAILTY SATU KOMPONEN DALAM ANALISIS DATA SURVIVAL DUA LEVEL
In survival analysis, it�s known a hazard function. It�s a risk or rate of an individual get
an event with one conditional, that individual survives until an event occurs. The hazard function
may depend on observed risk variables but usually not all variables are known or measurable.
This unknown factor of the hazard function is usually termed the individual heterogeneity or
frailty. In its simplest form, a frailty is an unobserved random factor that modifies
multiplicatively the hazard function of an individual or group or cluster of individuals. In this
thesis will be discussed about lognormal frailty model, an extension of Cox regression.
Hierarchical likelihood method will be used to estimate the regression coefficients and to find the
effect of frailty in the two level survival data
PENENTUAN HARGA OPSI BELI TIPE EROPA DENGAN RETURN ASET BERDISTRIBUSI NORMAL TRUNCATED
In stock and options trading, exchanges often imposed restrictions on the
daily price changes of an asset. As a result, the range of asset returns (in
logarithmic form) are no longer in the interval (- �, �), but truncated at the
bottom and top. Consequently returns no longer normally distributed, but
normally truncated distribution. Therefore, in this thesis will be discussed
regarding the European option pricing using Normal Truncated Distribution on
asset returns.
Furthermore, we compare the option price obtained by the normal
truncated distribution approach and the Black-Scholes model with option�s
market price. As a result, option pricing using normal truncated distribution
closer to the market price than the Black-Scholes model.. So we can conclude
empirically, the theory of option pricing models with normal truncated
distribution approach suitable for the option that has restrictions on its stock
price changes
ANALISIS TEKNIKAL SAHAM MENGGUNAKAN VARIABLE INDEX DYNAMIC AVERAGE (VIDYA)
Our financial and market action change every minute of every day. These
markets are dynamic because traders constantly adjust to changing perceptions
and participants. Therefore we need dynamic indicators that vary the time periode
used in analyzing market action. Variable Index Dynamic Average (VIDYA) is an
indicator that adapted Exponential Moving Average (EMA) that can dynamically
follow the movements of stock prices. Equal as Exponential Moving Average
(EMA), VIDYA also need weight in its calculation methods. In this paper, the
weight of EMA is used to determine the weight of VIDYA. VIDYA can be
calculated using three different methods, such as standard deviation, Chande
Momentum Oscillator (CMO), and coefficient of determination. These calculation
method is used to determine the volatility index that worth to predict stock price
movements and predict the trend in the future. In addition, VIDYA can be used as
trading strategy and determine buy signal or sell signal that using the breakout
point.
Keyword: technical analysis, volatility index, exponential moving average,
standard deviation, coeffitient of determination, momentum indicato
PENENTUAN HARGA OPSI EROPA MODEL TRINOMIAL DENGAN TEKNIK EKSTRAPOLASI
Research on how option pricing has continued to experienced over time. One of them is by describing stock price movements that follow the trinomial tree model. With this model, it is assumed that the movement of stock prices for the period ahead following three conditions: stock prices will increase, tend to constant, or it will decline. However, the results have a slow convergence so it is required a method to accelerate the convergence with the extrapolation. A frequently used method of extrapolation is the Richardson extrapolation technique which is quite popular extrapolation technique. The initial idea of the use of Richardson extrapolation technique is to do elimination on some early part of the asymptotic expansion from approached function that depends on the stepsize line to get a better approach
PERBANDINGAN MODEL REGRESI NONPARAMETRIK SPLINE DAN REGRESI NONPARAMETRIK KERNEL
Regression analysis is a statistical tool that is widely used to determine the
relationship between a pair of variables or more. Regression analysis is
divided into two, namely parametric regression and nonparametric
regression. Nonparametric regression has several smoothing methods, such
as spline and kernel regression. Its main purpose is to compare the two
methods for estimating the nonparametric regression model. The data were
used to compare the two methods of toddler growth data
APLIKASI GENERALIZED RIDGE REGRESSION UNTUK MENGATASI MASALAH MULTIKOLINEARITAS
Least square method is one of parameter estimation method, it is a method
for estimating regression coefficient. If any of classical regression assumption,
that is no multicollinearity is not met, parameter estimation using least square
method becomes less valid, even if there is perfect multicollinearity then it causes
beta parameters can�t be estimated. Linear relationship between the independent
variables causes the variance parameter beta becomes large, the error was large.
In fact, the estimated value we desired is a small variance and error.
For handling this multicollinearity problem, one of the way is using ridge
regression. The concept of ridge regression is by adding a k biased constant
which is a diagonal matrix, to the correlation matrix ' X X . In this paper we will
discuss one of the k parameter estimation methods, namely Generalized Ridge
Regression. This method obtain the k ridge parameter that is not a single
parameter but multiple k ridge parameters. Those k ridge parameters are different
for each independent variables
TEKNIK EKSTRAPOLASI RICHARDSON BERULANG PADA MODEL BINOMIAL FLEKSIBEL UNTUK MENENTUKAN HARGA OPSI JUAL AMERIKA
This thesis presents repeated Richardson extrapolation for pricing
American put option. We apply Richardson extrapolation on the sequence of
approximation of option value for accelerating the rate of its convergence. First,
we define the sequence of approximation using flexible binomial model. A
number of time step used in this scheme are based on the stepsize characterized by
sequence of integers. Second, we extrapolate the sequence of approximation
repeatedly. As the result, repeated Richardson extrapolation technique works on
flexible binomial model can be used to accelerate the sequence of approximation
produced by this scheme so that we merely need a less of time step for pricing
option